As one of its campaigns for individuals to have an emotional attachment to their drink, Coke has introduced a promotional strategy that involves personal names printed on a Coca-Cola can. This strategy seems to be working with a certain quarter of the society who feel a sense of pride with having their personal names on a Coca-Cola can. However, there have been some who have felt that KBL wasn’t fair in their determination of the choice of name to include on a Coke can. Some of those individuals whose names have been left out feel aggrieved and want this injustice to be rectified as soon as possible. They are in particular aggrieved that some undeserving names have made it to the Coke can while the deserving ones have been left out. As one who isn’t interested in their name appearing I thought I should volunteer my services to provide an answer to the top 100 names which should appear on the Coke can. My selection is based on some statistical work on names that I have done in the past.

For this study a database of names was compiled. The names were collected from diverse sources amongst these being: graduation name lists, school class lists, examination result lists for both primary and secondary (junior and secondary school) downloaded from the Botswana Ministry of Education and others scanned and transcribed from the Botswana’s Examination Unit. The database has 955,219 names. By names we are making no distinction between first names, middle names and surnames. All of these are counted as names. In our qualitative analysis of Setswana names there appears to be no compelling argument to treat first names differently from surnames since surnames are actually someone’s first name. Nevertheless, distinguishing the function of names could yield different results. The processing of data is conducted using Wordsmith Tools software which is an integrated suite of three main programs: Word list, Concord and Keywords. The Word list, tool can be used to produce word lists or word-cluster lists from a text and render the results alphabetically or by frequency order. It can also calculate word spread across a variety of texts, that is, render results on the basis of their spread in different texts. In this column we use the frequency analysis of the entire database. Our analysis borrows analytical techniques from corpus linguistics and analyses the names through frequency counts. Frequency counts record the number of times each name occurs in a text. Frequency analysis – performed intensively over the past 90 years – has been popularised by studies in corpus and lexicographic studies. A crucial point about a name is how frequent it is. Frequent names a) typify the naming practices of a community. b) unearth whether communities still use large numbers of colonial names or whether they have heeled away from such names. c) reveal if names with a certain semantic bend are favoured by a community of speakers. d) in a diachronic study reveal changing name practices within a community. e) frequency analysis of names offer a more reliable measure of spelling variation of the same name (For instance, Tshepo and Tshepho; Lorato and Lerato). Frequency lists are therefore interesting tools of studying names since they reveal which names are commonly used. We start this analysis by giving a panoramic overview of the data. The data has 955,219 tokens (individual counts of names including repetitions) and 49,385 types (unique counts of each name). We start this analysis by giving discussing the most frequent 100 Botswana names & only list the most frequent 25. The most frequent 25 names extracted on the basis of frequency in the entire corpus are:

The top 100 names reveal some intriguing naming patterns amongst the Batswana. First, the names suggest that Batswana consider children as gifts. The following names together with their ranks reveal this phenomenon: Mpho (a gift), Kabelo (that which has been given me), Neo (what is given) Kabo (that which is given), Kefilwe (I have been given), Gofaone (It is him (God) who gives), Keneilwe (I have been given), Omphile (He (God) has given me), Tshegofatso (a blessing), Refilwe (We have been given), Keabetswe (I have been given), Kamogelo (receiving), Dineo (gifts), 62. Onkabetse (He (God) has given to me), Onneile (He (God) has given me), Goabaone (It is him (God) who gives), Keamogetse (I have received). Second, many names express gratitude for the child who has been born. Amongst these names are Tebogo (gratitude), Kelebogile (I am thankful), Lebogang (give thanks), Malebogo (thanks), Kealeboga (I am thankful), Keitumetse (I am thankful/I am happy), Olebogeng (thank him (God)). There is also a cluster of names of virtuous qualities espoused by the community, either because of its religion or culture. Amongst these are: Kagiso (peace), Boitumelo (happiness), Tshepo/Tshepho (trust), Lorato (love), Tumelo (faith), Kgomotso (comfort), Thabo (joy), Tsholofelo (hope), Katlego (success), Tshiamo(righteousness), Khumo (wealth), Bonolo (gentleness), Kitso (knowledge/wisdom), and Phenyo (victory). Other names celebrate the coming of a new born. Amongst these are Keitumetse (I am thankful/I am happy), Itumeleng (rejoice/celebrate), Obakeng (praise him (God)), Thabang (be glad), Maipelo (one’s source of pride and joy), Pako (a song of praise), and Bakang (praise). Other names are clearly religious, revealing the Batswana’s belief in the supernatural that children are a gift from God. Amongst these are; Gaone (his (God)), Onalenna (he (God) is with me), Gofaone (it is him (God) who gives), Goitseone (it is him (God) who knows), Thapelo (prayer), Tumelo (faith), Thatayaone (his (God) will), Oarabile (He (God) has answered), Mmoloki (a saviour), Goitsemodimo (God knows), Goabaone (it is him (God) who gives), Onalethata (he (God) has strength), Othusitse (he (God) has helped) and Olebile (he (God) is watching). What the analysis above illustrates is that on the basis of frequency some of the critical typical names amongst the Batswana can be unearthed and they can be clustered thematically as attempted here. Batswana can now complain to KBL based on the results discussed here!